Mobile Robot Combination Autonomous Behavior Strategy to Inspect Hazardous Gases in Relatively Narrow Man–Machine Environment

Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especially in a relatively narrow man–machine dynamic environments such as warehouses and laboratories.In this study,human and robot behaviors in man–machine environments are analyzed,and a man–machine social force model is established to study the robot obstacle avoidance speed.Four typical man–machine behavior patterns are investigated to design the robot behavior strategy.Based on the social force model and man–machine behavior patterns,the fuzzy-PID trajectory tracking control method and the autonomous obstacle avoidance behavior strategy of the mobile robot in inspecting hazardous gases in a relatively narrow man–machine dynamic environment are proposed to determine the optimal robot speed for obstacle avoidance.The simulation analysis results show that compared with the traditional PID control method,the proposed controller has a position error of less than 0.098 m,an angle error of less than 0.088 rad,a smaller steady-state error,and a shorter convergence time.The crossing and encountering pattern experiment results show that the proposed behavior strategy ensures that the robot maintains a safe distance from humans while performing trajectory tracking.This research proposes a combination autonomous behavior strategy for mobile robots inspecting hazardous gases,ensuring that the robot maintains the optimal speed to achieve dynamic obstacle avoidance,reducing human anxiety and increasing comfort in a relatively narrow man–machine environment.

CREATION OF OPTIMAL MOVEMENT STRATEGY OF PLURAL MOVING OB-JECTS BY GA

The topographic information of a closed world is expressed as a graph. The plural mov- ingobjects which go and back in it according to a single moving strategy are supposed.The moving strategy is expressed by numerical values as a decision table. Coding is performed with this table as chromosomes, and this is optimized by using genetic algorithm. These environments were realized on a computer, and the simulation was carried out. As the result, the learning of the method to act so that moving objects do not obstruct mutually was recognized, and it was confirmed that these methods are effective for optimizing moving strategy.

Vibration coupling effects and machining behavior of ultrasonic vibration plate device for creep-feed grinding of Inconel 718 nickel-based superalloy

Ultrasonic vibration-assisted grinding(UVAG)is an effective and promising method for machining of hard-to-cut materials.This article proposed an ultrasonic vibration plate device enabling the longitudinal full-wave and transverse half-wave(L2T1)vibration mode for UVAG.The characteristics of two-dimensional coupled vibration in different directions were analyzed on the basis of apparent elastic method and finite element method.Furthermore,a correction factor was applied to correct the frequency error caused by the apparent elastic method.Finally,the comparative experiments between the conventional creep-feed grinding and UVAG of Inconel 718 nickel-based superalloy were carried out.The results indicate that the apparent elastic method with the correction factor is accurate for the design of plate device under the L2T1 vibration mode.Compared with the conventional creep-feed grinding,the UVAG causes the reduction of grinding force and the improvement of machined surface quality of Inconel 718 nickel-based superalloy.Furthermore,under the current experimental conditions,the optimal ultrasonic vibration amplitude is determined as 6μm,with which the minimum surface roughness is achieved.